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COMMUNICATION AND COMPUTATION ARCHITECTURES FOR DISTRIBUTED WIRELESS SENSOR NETWORKS AND INTERNET OF THINGS
Title
COMMUNICATION AND COMPUTATION ARCHITECTURES FOR DISTRIBUTED WIRELESS SENSOR NETWORKS AND INTERNET OF THINGS
Creator
Yi, Won-jae
Date
2017, 2017-07
Description
Real-time data communication has been viral since the era of the smartphone rose to prominence in this decade. All communications from human...
Show moreReal-time data communication has been viral since the era of the smartphone rose to prominence in this decade. All communications from human to human, from device to human, and from device to device are handled over the Internet connection either through a mobile Internet service provider or Wi-Fi, which enables information exchange including weather service, road traffic conditions, news alerts, package tracking notifications. By looking at different perspectives of the role of a smartphone, it reveals itself as an ideal device to mobilize critical user data to construct a real-time monitoring application such as in remote healthcare and home automation systems. Not only can the smartphone handle real-time data transmissions, but it can also handle real-time computations on the device itself by utilizing its embedded CPU. This dissertation is a comprehensive study of the investigation, exploration and experimentation on a real-time health monitoring system where quality of life can be improved when the conventional system may affect and hamper regular daily activities. The design flow of this system is based on the Internet connection where any device that is communicatively associated with the smartphone can be connected to the Internet. By utilizing the Android smartphone, not only does the system gain real-time data transmission capability, but it also obtains flexibility to communicate with different types of sensors and platforms through multiple wireless protocols. This system is highly adaptable to the currently trending Internet of Things (IoT) standards, where significantly increasing anticipation over its social impact, where it can assist populations in rural and distant areas for healthcare, day-to-day activity monitoring, and prevention against hazardous conditions for workers. The system architecture introduced in this research is focused on reconfigurability and compatibility of wireless sensors where they are independent from a certain platform in which sensors are not limited to medical devices but also detect movement, location, climate condition and any other sensor for analyzing the environment. Four major components are introduced in this research including wireless sensor nodes, a central sensor data processing and communication node, an Android application, and a central database server. They are discussed and explored to seek for solutions to improve and enhance features in the fundamental system design. Communication and computation processing capabilities are evaluated for all major components for practical usage of the system for different case studies. Also as a quantitative case study, a posture and fall detection system is presented which determines the patient's activities, medical conditions and the cause of an emergency event through the integration of all system architecture components. Adapting the IoT system is also explored in this dissertation by introducing a protocol standard to improve data transmission efficiency and to enable cross-platform compatibility of wireless devices. In addition to improving system efficiency, a study on data security issues and assessment on sensor data has been explored by implementing a proposed security scheme to each major component within the real-time mobile monitoring system. Also, a concept of Quality-of-Service (QoS) for mobile monitoring system using a wireless sensor network has been investigated to provide a solution to prioritize sensor data transmissions based on the results obtained from the sensor data assessment application. The proposed solutions can be either implemented on or under the application layer.
Ph.D. in Computer Engineering, July 2017
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MOBILE ANDROID SENSOR SYSTEM FOR REAL-TIME PATIENT MONITORING AND HEALTHCARE APPLICATION
Title
MOBILE ANDROID SENSOR SYSTEM FOR REAL-TIME PATIENT MONITORING AND HEALTHCARE APPLICATION
Creator
Yi, Won-jae
Date
2012-04-25, 2012-05
Description
A system using Android devices that collects, displays sensor data on the screen and streams to the central server in real-time is presented...
Show moreA system using Android devices that collects, displays sensor data on the screen and streams to the central server in real-time is presented in this research. Common Android devices, such as smartphones and tablets, are considered for this system to demonstrate its flexibility and compatibility of the application on any Android device. Bluetooth and wireless Internet connections are used for data transmission among the devices. Also, using Near Field Communication (NFC) technology on the smartphone, the system constructs a more efficient and convenient mechanism to achieve an automatic Bluetooth connection and an automatic application execution. This system is beneficial on Body Sensor Network (BSN) establishments for medical healthcare applications by adding wireless technology. Various types of sensors can be adapted to monitor a patient’s status in real-time. For demonstration purposes, an accelerometer, a temperature sensor and vital signs signal sensor data, including electrocardiography (ECG), blood pressure, electroencephalography (EEG) and respiration, are used to perform the experiment to provide fundamentals of remote patient diagnosis. Raw sensor data is interpreted to either graphical or text notations to be presented on the Android device and the central server. Furthermore, a Java-based central server application is introduced to demonstrate communication with the Android system for data storage and analysis through Internet connections. This system is capable of data transmission in real-time without exploiting system resources for data collection and interpretation. This system is also can be further extended for additional sensors, such as a sweatiness sensor, an electromyography (EMG) sensor, a glucose sensor and more for enhanced patient status diagnosis.
M.S. in Computer Engineering, May 2012
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